code: def test_rca_supervised(self):
      seed = np.random.RandomState(1234)
      rca = RCA_Supervised(
          n_components=2, n_chunks=30, chunk_size=2, random_state=seed
      )
      rca.fit(self.X, self.y)
      res_1 = rca.transform(self.X)
  
      seed = np.random.RandomState(1234)
      rca = RCA_Supervised(
          n_components=2, n_chunks=30, chunk_size=2, random_state=seed
      )
      res_2 = rca.fit_transform(self.X, self.y)
  
      assert_array_almost_equal(res_1, res_2)
  
file_path: metric-learn/test/test_fit_transform.py
imports: import unittest
  import numpy
  from sklearn.datasets import load_iris
  from numpy.testing import assert_array_almost_equal
  from metric_learn import LMNN, NCA, LFDA, Covariance, MLKR, LSML_Supervised, ITML_Supervised, SDML_Supervised, RCA_Supervised, MMC_Supervised
label_desc: Use image node_id 9 for calling the TestFitTransform obj's underlying member method code with example usage: obj.test_rca_supervised() without return types